mirror of
https://github.com/OPM/opm-simulators.git
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303 lines
9.1 KiB
C++
303 lines
9.1 KiB
C++
/*
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Copyright 2012 SINTEF ICT, Applied Mathematics.
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This file is part of the Open Porous Media project (OPM).
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OPM is free software: you can redistribute it and/or modify
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it under the terms of the GNU General Public License as published by
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the Free Software Foundation, either version 3 of the License, or
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(at your option) any later version.
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OPM is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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GNU General Public License for more details.
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You should have received a copy of the GNU General Public License
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along with OPM. If not, see <http://www.gnu.org/licenses/>.
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*/
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#if HAVE_CONFIG_H
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#include "config.h"
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#endif
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#include <opm/core/linalg/LinearSolverIstl.hpp>
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#include <opm/core/utility/have_boost_redef.hpp>
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// TODO: clean up includes.
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#include <dune/common/deprecated.hh>
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#include <dune/istl/bvector.hh>
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#include <dune/istl/bcrsmatrix.hh>
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#include <dune/istl/operators.hh>
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#include <dune/istl/io.hh>
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#include <dune/istl/preconditioners.hh>
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#include <dune/istl/solvers.hh>
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#include <dune/istl/paamg/amg.hh>
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#include <stdexcept>
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namespace Opm
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{
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using namespace Dune; // While not great, it's okay in a cpp file like this.
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namespace {
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typedef FieldVector<double, 1 > VectorBlockType;
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typedef FieldMatrix<double, 1, 1> MatrixBlockType;
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typedef BCRSMatrix <MatrixBlockType> Mat;
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typedef BlockVector<VectorBlockType> Vector;
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typedef MatrixAdapter<Mat,Vector,Vector> Operator;
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LinearSolverInterface::LinearSolverReport
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solveCG_ILU0(const Mat& A, Vector& x, Vector& b, double tolerance, int maxit, int verbosity);
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LinearSolverInterface::LinearSolverReport
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solveCG_AMG(const Mat& A, Vector& x, Vector& b, double tolerance, int maxit, int verbosity);
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LinearSolverInterface::LinearSolverReport
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solveBiCGStab_ILU0(const Mat& A, Vector& x, Vector& b, double tolerance, int maxit, int verbosity);
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} // anonymous namespace
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LinearSolverIstl::LinearSolverIstl()
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: linsolver_residual_tolerance_(1e-8),
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linsolver_verbosity_(0),
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linsolver_type_(CG_AMG),
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linsolver_save_system_(false),
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linsolver_max_iterations_(0)
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{
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}
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LinearSolverIstl::LinearSolverIstl(const parameter::ParameterGroup& param)
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: linsolver_residual_tolerance_(1e-8),
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linsolver_verbosity_(0),
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linsolver_type_(CG_AMG),
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linsolver_save_system_(false),
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linsolver_max_iterations_(0)
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{
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linsolver_residual_tolerance_ = param.getDefault("linsolver_residual_tolerance", linsolver_residual_tolerance_);
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linsolver_verbosity_ = param.getDefault("linsolver_verbosity", linsolver_verbosity_);
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linsolver_type_ = LinsolverType(param.getDefault("linsolver_type", int(linsolver_type_)));
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linsolver_save_system_ = param.getDefault("linsolver_save_system", linsolver_save_system_);
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if (linsolver_save_system_) {
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linsolver_save_filename_ = param.getDefault("linsolver_save_filename", std::string("linsys"));
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}
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linsolver_max_iterations_ = param.getDefault("linsolver_max_iterations", linsolver_max_iterations_);
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}
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LinearSolverIstl::~LinearSolverIstl()
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{
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}
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LinearSolverInterface::LinearSolverReport
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LinearSolverIstl::solve(const int size,
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const int nonzeros,
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const int* ia,
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const int* ja,
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const double* sa,
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const double* rhs,
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double* solution) const
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{
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// Build Istl structures from input.
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// System matrix
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Mat A(size, size, nonzeros, Mat::row_wise);
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for (Mat::CreateIterator row = A.createbegin(); row != A.createend(); ++row) {
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int ri = row.index();
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for (int i = ia[ri]; i < ia[ri + 1]; ++i) {
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row.insert(ja[i]);
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}
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}
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for (int ri = 0; ri < size; ++ri) {
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for (int i = ia[ri]; i < ia[ri + 1]; ++i) {
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A[ri][ja[i]] = sa[i];
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}
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}
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// System RHS
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Vector b(size);
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std::copy(rhs, rhs + size, b.begin());
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// System solution
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Vector x(size);
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x = 0.0;
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if (linsolver_save_system_)
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{
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// Save system to files.
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writeMatrixToMatlab(A, linsolver_save_filename_ + "-mat");
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std::string rhsfile(linsolver_save_filename_ + "-rhs");
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std::ofstream rhsf(rhsfile.c_str());
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rhsf.precision(15);
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rhsf.setf(std::ios::scientific | std::ios::showpos);
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std::copy(b.begin(), b.end(),
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std::ostream_iterator<VectorBlockType>(rhsf, "\n"));
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}
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int maxit = linsolver_max_iterations_;
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if (maxit == 0) {
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maxit = A.N();
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}
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LinearSolverReport res;
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switch (linsolver_type_) {
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case CG_ILU0:
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res = solveCG_ILU0(A, x, b, linsolver_residual_tolerance_, maxit, linsolver_verbosity_);
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break;
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case CG_AMG:
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res = solveCG_AMG(A, x, b, linsolver_residual_tolerance_, maxit, linsolver_verbosity_);
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break;
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case BiCGStab_ILU0:
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res = solveBiCGStab_ILU0(A, x, b, linsolver_residual_tolerance_, maxit, linsolver_verbosity_);
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break;
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default:
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std::cerr << "Unknown linsolver_type: " << int(linsolver_type_) << '\n';
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throw std::runtime_error("Unknown linsolver_type");
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}
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std::copy(x.begin(), x.end(), solution);
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return res;
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}
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void LinearSolverIstl::setTolerance(const double tol)
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{
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linsolver_residual_tolerance_ = tol;
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}
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double LinearSolverIstl::getTolerance() const
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{
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return linsolver_residual_tolerance_;
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}
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namespace
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{
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LinearSolverInterface::LinearSolverReport
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solveCG_ILU0(const Mat& A, Vector& x, Vector& b, double tolerance, int maxit, int verbosity)
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{
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Operator opA(A);
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// Construct preconditioner.
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SeqILU0<Mat,Vector,Vector> precond(A, 1.0);
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// Construct linear solver.
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CGSolver<Vector> linsolve(opA, precond, tolerance, maxit, verbosity);
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// Solve system.
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InverseOperatorResult result;
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linsolve.apply(x, b, result);
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// Output results.
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LinearSolverInterface::LinearSolverReport res;
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res.converged = result.converged;
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res.iterations = result.iterations;
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res.residual_reduction = result.reduction;
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return res;
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}
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LinearSolverInterface::LinearSolverReport
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solveCG_AMG(const Mat& A, Vector& x, Vector& b, double tolerance, int maxit, int verbosity)
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{
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// Solve with AMG solver.
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#define FIRST_DIAGONAL 1
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#define SYMMETRIC 1
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#define SMOOTHER_ILU 1
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#define ANISOTROPIC_3D 0
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#if FIRST_DIAGONAL
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typedef Amg::FirstDiagonal CouplingMetric;
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#else
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typedef Amg::RowSum CouplingMetric;
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#endif
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#if SYMMETRIC
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typedef Amg::SymmetricCriterion<Mat,CouplingMetric> CriterionBase;
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#else
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typedef Amg::UnSymmetricCriterion<Mat,CouplingMetric> CriterionBase;
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#endif
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#if SMOOTHER_ILU
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typedef SeqILU0<Mat,Vector,Vector> Smoother;
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#else
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typedef SeqSSOR<Mat,Vector,Vector> Smoother;
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#endif
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typedef Amg::CoarsenCriterion<CriterionBase> Criterion;
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typedef Amg::AMG<Operator,Vector,Smoother> Precond;
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Operator opA(A);
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// Construct preconditioner.
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double relax = 1;
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Precond::SmootherArgs smootherArgs;
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smootherArgs.relaxationFactor = relax;
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Criterion criterion;
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criterion.setDebugLevel(verbosity);
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#if ANISOTROPIC_3D
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criterion.setDefaultValuesAnisotropic(3, 2);
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#endif
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Precond precond(opA, criterion, smootherArgs);
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// Construct linear solver.
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CGSolver<Vector> linsolve(opA, precond, tolerance, maxit, verbosity);
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// Solve system.
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InverseOperatorResult result;
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linsolve.apply(x, b, result);
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// Output results.
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LinearSolverInterface::LinearSolverReport res;
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res.converged = result.converged;
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res.iterations = result.iterations;
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res.residual_reduction = result.reduction;
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return res;
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}
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LinearSolverInterface::LinearSolverReport
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solveBiCGStab_ILU0(const Mat& A, Vector& x, Vector& b, double tolerance, int maxit, int verbosity)
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{
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Operator opA(A);
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// Construct preconditioner.
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SeqILU0<Mat,Vector,Vector> precond(A, 1.0);
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// Construct linear solver.
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BiCGSTABSolver<Vector> linsolve(opA, precond, tolerance, maxit, verbosity);
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// Solve system.
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InverseOperatorResult result;
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linsolve.apply(x, b, result);
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// Output results.
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LinearSolverInterface::LinearSolverReport res;
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res.converged = result.converged;
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res.iterations = result.iterations;
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res.residual_reduction = result.reduction;
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return res;
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}
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} // anonymous namespace
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} // namespace Opm
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